pith. sign in

arxiv: 2605.27507 · v1 · pith:HJ43NN7Hnew · submitted 2026-05-26 · 🌌 astro-ph.GA · astro-ph.HE

BlackHoleWeather -- Chaotic cold accretion across the meso-scale: Morphology and thermodynamics

Pith reviewed 2026-06-29 16:51 UTC · model grok-4.3

classification 🌌 astro-ph.GA astro-ph.HE
keywords chaotic cold accretionthermal instabilitysupermassive black hole feedingmultiphase gasturbulencegalaxy groupshydrodynamic simulationsblack hole weather
0
0 comments X

The pith

Modest turbulence variations can switch a hot halo from extended stormy cold gas accretion to compact rainy accretion around the supermassive black hole.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper examines turbulence-driven condensation in hot group-scale halos using 3D hydrodynamic simulations that include cooling and subsonic stirring. It finds that stronger turbulence produces extended filaments of cold gas out to kiloparsec scales in a stormy pattern, while weaker turbulence leads to earlier but more centralized condensation within 100 parsecs in a rainy pattern. Both cases create a multiphase medium across huge ranges in density and temperature, and both boost the black hole accretion rate by up to 100 times the hot Bondi rate. The accretion boost depends more on how the cold structures connect to the center than on the total amount of cold gas. This establishes a multiscale picture of chaotic cold accretion for interpreting black hole feeding.

Core claim

In simulations of a hot intragroup halo with driven subsonic turbulence, the gas becomes thermally unstable and forms multiphase structures. Strong stirring creates an extended filament-rich rain to kpc radii that delays central accretion, while weak stirring yields compact rain mostly within 100 pc. The black hole accretion rate shows recurrent boosts up to 100 times the Bondi baseline in both cases, with only weak variation between regimes, indicating regulation by multiphase coupling efficiency rather than condensed mass alone.

What carries the argument

Turbulence level controlling the morphology of chaotic cold accretion, shifting between stormy extended and rainy centralized states via nonlinear thermal instability.

If this is right

  • The same halo can display different black hole weather states with only modest turbulence differences.
  • Black hole feeding rates are boosted similarly despite large differences in cold gas distribution.
  • Multiphase condensation spans 8-10 orders of magnitude in temperature and density.
  • At small scales, inflow involves a clumpy rotating torus.
  • Provides baseline for multiphase CCA interpretation.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Observed filament lengths in galaxy groups could serve as proxies for turbulence strength.
  • Including magnetic fields in future models might change the threshold between stormy and rainy regimes.
  • The weak dependence of accretion rate on turbulence suggests a robust self-regulation mechanism across environments.
  • This framework could extend to cluster-scale halos to predict AGN variability.

Load-bearing premise

The driven subsonic turbulence and radiative cooling in the hydrodynamic simulations represent the primary drivers of thermal instability and gas condensation in real halos.

What would settle it

Finding a galaxy group halo with measured low turbulence but extended cold filaments out to kpc scales, or high turbulence with only central cold gas, would contradict the predicted morphology shift.

Figures

Figures reproduced from arXiv: 2605.27507 by Ashkbiz Danehkar, Davide M. Brustio, Fabrizio Fiore, Filippo Barbani, Filippo M. Maccagni, Francesco Tombesi, Fred J. Jennings, Giovanni Stel, Martin Fournier, Massimo Gaspari, Olmo Piana, Pasquale Temi, Roberto Serafinelli, Valeria Olivares, Vieri Cammelli.

Figure 1
Figure 1. Figure 1: Simulation grid and SMBH sink scheme. The domain is decom￾posed into blocks (shown as a green square), which are recursively re￾fined towards the centre of the domain (each block contains 323 cells). The decreasing block size increases the effective resolution in the cen￾tral region, where the black hole sink is located. The black hole sink (shown in black) removes mass within a radius of four finest-level… view at source ↗
Figure 2
Figure 2. Figure 2: Thermodynamic properties of the simulated galaxy group at t = 0 Myr (black lines). Left: radial gas number density profile compared with observed electron densities from the ACCEPT database (Cavagnolo et al. 2009, pink circles). Right: normalised temperature profile (T/Tmax) as a function of r/Rvir, compared with early-type galaxies from the Chandra Galaxy Atlas (Kim et al. 2020, pink circles). The ICs are… view at source ↗
Figure 3
Figure 3. Figure 3: Radiative cooling function at solar metallicity used in our simu￾lations. The curve shows Λ(T) as a function of temperature, with tabu￾lated values from Schure et al. (2009) for T ≥ 104.2 K and the analytic fit given by Eq. (13) for T < 104.2 K. Cooling function includes metal￾line, recombination, bremsstrahlung and low temperature cooling; it is tabulated on a uniform grid in log T and interpolated during… view at source ↗
Figure 4
Figure 4. Figure 4: Gas density slices of the central 50 kpc region in the cca_high simulation. Rows show the time evolution from t/train = 1.5 (top) to t/train = 3 (bottom), while within each row the panels from left to right present a progressive zoom-in from the halo scale (macro) to the filamentary condensation region (meso) and finally to the innermost clumps (micro). The sequence reveals the characteristic morphology of… view at source ↗
Figure 5
Figure 5. Figure 5: Gas density slices of the central region in the cca_low simulation. Rows show the time evolution from t/train = 1.5 (top) to t/train = 3 (bottom), while within each row the panels from left to right present a zoom-in from the inner kiloparsec to 15 pc around the SMBH. At both epochs, the system hosts a dense, clumpy cold core on parsec scales, continuously fed by smoother filamentary inflows from larger ra… view at source ↗
Figure 6
Figure 6. Figure 6: Slices of the simulated galaxy group core for the cca_high (top row) and cca_low (bottom row) simulations at t/train = 3, showing temperature (left), pressure (middle), and velocity magnitude (right). The maps highlight the multiphase structure of the IGrM and the role of turbulence in driving thermodynamic fluctuations in the hot atmosphere, seeding local thermal instability and the condensation of cold g… view at source ↗
Figure 7
Figure 7. Figure 7: SMBH accretion rate M˙ normalised to the Bondi accretion rate M˙ B as a function of normalised time t/train for the cca_high (blue line, stormy weather) and the cca_low (cyan line, rainy weather) sim￾ulations, compared with the turbulence simulations (sunny weather) turb_high (red line) and turb_low (yellow line), with the radia￾tive cooling simulation cool (purple line) and with the idealised adi￾abatic s… view at source ↗
Figure 8
Figure 8. Figure 8: Mass-weighted radial profiles of gas density, temperature, thermal pressure, and velocity magnitude for simulations cca_high (top row) and cca_low (bottom row). The gas is divided into five temperature phases: hot, hard X-ray (red) and soft X-ray (orange), warm (violet), cold (blue) and molecular (cyan, see [PITH_FULL_IMAGE:figures/full_fig_p012_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: Mass-weighted density-temperature phase diagrams for the cool (blue), turb_high (red) and turb_low (orange) simulations. Dashed oblique lines indicate adiabatic (T ∝ n γ−1 = n 2/3 ) and isobaric (T ∝ n −1 ) relations. molecular regime. The phase plot at this stage shows gas popu￾lating mainly intermediate densities (n ∼ 1−102 cm−3 ) and tem￾peratures (T ∼ 104−5 K), forming a continuous bridge between the h… view at source ↗
Figure 10
Figure 10. Figure 10: Mass-weighted density–temperature phase diagrams for the cca_high (rows 1 and 3) and cca_low (rows 2 and 4) simulations. The first two rows show the time evolution at t/train = 0.1, 1, 2, 3, while the last two rows show the corresponding distributions at t/train = 3 in four radial ranges: 0 < r ≤ 0.1 kpc (micro-scale), 0.1 < r ≤ 1 kpc (meso-scale), 1 < r ≤ 10 kpc (inner macro-scale), and r > 10 kpc (outer… view at source ↗
Figure 11
Figure 11. Figure 11: Gas mass for cca_high (solid) and cca_low (dashed) sim￾ulations divided in molecular (cyan), cold (blue), warm (violet), soft (orange), and hard (red) X-ray gas and in different scales: macro, meso, inner macro and outer macro. that can heat up or disrupt the cold gas. At t < train the medium is dominated by the hot gas in both simulations (Mhot ≈ 104 M⊙). After t/train = 1 warm, cold and molecular gas st… view at source ↗
Figure 12
Figure 12. Figure 12: Probability density functions (PDFs) of gas density measured in three radial shells, spanning the micro, meso, and inner macro-scales. The top two rows show the evolution within the inner r ≤ 0.1 kpc region (micro-scale), the middle two rows correspond to 0.1 < r ≤ 1 kpc (meso-scale), and the bottom two rows to 1 < r ≤ 10 kpc (inner macro-scale). For each radial shell, the upper row displays the cca_high … view at source ↗
Figure 13
Figure 13. Figure 13: Cartoon scheme illustrating a possible evolutionary sequence driven by the interplay between turbulence and gas condensation. Rainy phase (cca_low): in a low-turbulence state, cold clumps and filaments are concentrated near the nucleus, leading to coherent accretion and a centrally confined cold phase. Sunny phase (turb_low/turb_high): increased turbulent stirring redistributes the cold gas and temporaril… view at source ↗
read the original abstract

Supermassive black holes (SMBHs) self-regulate galaxies, groups, and clusters, yet the pathway transporting gas from halo scales to sub-pc radii remains debated. In hot stratified atmospheres, subsonic turbulence can trigger nonlinear thermal instability and a multiphase condensation cascade, producing chaotic time-variable BH `weather'. A key missing link is how the meso-scale connects halo rain to nuclear inflow. We study turbulence-driven condensation and chaotic cold accretion (CCA) in a group-scale halo, quantifying how the stirring level shapes multiphase morphology, thermodynamics, and SMBH feeding. We ran 3D hydrodynamic hyper-zoom simulations with a GPU-accelerated code, including cooling and driven subsonic turbulence in a hot intragroup halo. Two endpoint runs bracket weak and strong stirring, capturing distinct BH weather states. In both regimes the atmosphere becomes thermally unstable and develops a multiphase medium spanning 8-10 dex in temperature and density. Strong stirring delays cold gas accretion and sustains an extended filament-rich rain pattern to kpc radii (`stormy' CCA), with broader thermodynamic distributions beyond the nucleus. Weak stirring triggers earlier condensation but yields a more compact rain, with most cold gas confined within 100 pc (`rainy' CCA). At micro-scales the inflow is partly mediated by a clumpy rotating torus. Despite large differences in condensed cold mass, the BH accretion rate is recurrently boosted by up to 100x above the hot-mode Bondi baseline and varies weakly between the weather regimes, indicating that feeding is regulated primarily by how efficiently multiphase structures couple to the central inflow. Modest turbulence changes are sufficient to shift the same hot halo between stormy (extended) and rainy (centralized) BH weather, providing a quantitative multiscale baseline for interpreting multiphase CCA and SMBH feeding.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 1 minor

Summary. The manuscript presents 3D hydrodynamic simulations of a group-scale hot halo with cooling and driven subsonic turbulence at two endpoint stirring amplitudes. It reports that strong stirring produces extended filamentary 'stormy' CCA while weak stirring yields compact 'rainy' CCA, with both regimes developing multiphase gas over 8-10 dex in T and rho; despite large differences in cold mass, the central BH accretion rate is recurrently boosted by up to 100x above the hot-mode Bondi value and varies only weakly between regimes, implying regulation by multiphase inflow coupling. The work positions modest turbulence variations as sufficient to shift the same halo between these weather states, offering a multiscale baseline for CCA and SMBH feeding.

Significance. If the hydro results prove robust, the quantitative comparison of morphology, thermodynamics, and feeding across stirring levels supplies a useful meso-scale reference for interpreting multiphase condensation and nuclear inflow in stratified halos. The direct numerical experiments (two endpoint runs) and the finding of similar accretion boosts despite differing cold-gas distributions are strengths that could aid observational interpretation of CCA.

major comments (2)
  1. [Abstract / simulation description] The central claim that turbulence amplitude alone controls the shift between extended-filament ('stormy') and compact ('rainy') CCA morphologies rests on pure hydrodynamics plus cooling; the simulation setup omits magnetic fields, which are known to modify the nonlinear thermal instability threshold, condensation geometry, and cold-gas coupling via anisotropic conduction and tension. This omission is load-bearing for the generalization to a 'quantitative multiscale baseline' because the reported distinction may not persist when these effects are included.
  2. [Abstract / results] The reported accretion-rate boosts (up to 100x) and weak variation between regimes are presented without reference to numerical resolution, convergence tests, or error analysis; given that the morphology and thermodynamic distributions are the primary observables, it is unclear whether the differences between the weak- and strong-stirring cases are numerically converged.
minor comments (1)
  1. The phrase 'hyper-zoom simulations' and the GPU-accelerated code are mentioned without a specific reference or method citation; adding this would improve reproducibility.

Simulated Author's Rebuttal

2 responses · 1 unresolved

We thank the referee for the constructive comments. We respond point by point to the major comments below.

read point-by-point responses
  1. Referee: [Abstract / simulation description] The central claim that turbulence amplitude alone controls the shift between extended-filament ('stormy') and compact ('rainy') CCA morphologies rests on pure hydrodynamics plus cooling; the simulation setup omits magnetic fields, which are known to modify the nonlinear thermal instability threshold, condensation geometry, and cold-gas coupling via anisotropic conduction and tension. This omission is load-bearing for the generalization to a 'quantitative multiscale baseline' because the reported distinction may not persist when these effects are included.

    Authors: We agree that the simulations are purely hydrodynamic and that magnetic fields can alter thermal instability thresholds, condensation geometry, and cold-gas dynamics. The manuscript presents a controlled hydrodynamical experiment isolating the role of turbulence amplitude. We will revise the abstract, introduction, and discussion to explicitly qualify the results as a hydrodynamic baseline and to note that the stormy/rainy distinction may change once MHD effects are included. revision: yes

  2. Referee: [Abstract / results] The reported accretion-rate boosts (up to 100x) and weak variation between regimes are presented without reference to numerical resolution, convergence tests, or error analysis; given that the morphology and thermodynamic distributions are the primary observables, it is unclear whether the differences between the weak- and strong-stirring cases are numerically converged.

    Authors: Both runs employed identical numerical resolution chosen to capture the cooling length across the reported dynamic range. No dedicated convergence study was reported in the submitted manuscript. We will add a methods paragraph describing the grid resolution and arguing that the qualitative morphology shift and order-of-magnitude accretion boost are robust at this resolution, while acknowledging that quantitative accretion-rate values would benefit from explicit convergence tests. revision: partial

standing simulated objections not resolved
  • Whether the reported distinction between stormy and rainy CCA morphologies persists once magnetic fields, anisotropic conduction, and tension are included, as this requires new MHD simulations.

Circularity Check

0 steps flagged

No significant circularity: claims emerge from direct numerical experiments

full rationale

The paper's central claims about turbulence-driven shifts between stormy and rainy CCA states are outputs of two endpoint 3D hydrodynamic simulations that evolve cooling and driven subsonic turbulence from initial conditions in a stratified halo. No load-bearing step reduces by construction to a fitted parameter, self-citation chain, or renamed input; the morphology, thermodynamic distributions, and accretion rates are measured directly from the evolved fields rather than presupposed. The multiscale baseline is therefore an independent result of the numerical setup, not a self-referential reduction.

Axiom & Free-Parameter Ledger

2 free parameters · 2 axioms · 0 invented entities

The central claim rests on standard hydrodynamic and cooling assumptions from prior literature plus the modeling choice of two discrete turbulence amplitudes; no new entities are introduced.

free parameters (2)
  • turbulence stirring amplitude
    Two endpoint values chosen to bracket weak and strong regimes
  • cooling function implementation
    Standard but unspecified details control condensation timing
axioms (2)
  • domain assumption Subsonic turbulence triggers nonlinear thermal instability and multiphase condensation cascade
    Invoked as the mechanism producing cold gas in the hot halo
  • domain assumption Initial hot stratified intragroup atmosphere
    Starting condition for all runs

pith-pipeline@v0.9.1-grok · 5926 in / 1362 out tokens · 61229 ms · 2026-06-29T16:51:12.250980+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

112 extracted references · 4 canonical work pages · 2 internal anchors

  1. [1]

    E., Mantz, A

    Abdulla, Z., Carlstrom, J. E., Mantz, A. B., et al. 2019, ApJ, 871, 195

  2. [2]

    Balbus, S. A. & Hawley, J. F. 1998, Reviews of Modern Physics, 70, 1

  3. [3]

    2026, A&A, Submitted

    Barbani, F., Gaspari, M., Cammelli, V ., & et al. 2026, A&A, Submitted

  4. [4]

    2023, MNRAS, 524, 4091

    Barbani, F., Pascale, R., Marinacci, F., et al. 2023, MNRAS, 524, 4091

  5. [5]

    2025, A&A, 697, A121

    Barbani, F., Pascale, R., Marinacci, F., et al. 2025, A&A, 697, A121

  6. [6]

    1952, MNRAS, 112, 195

    Bondi, H. 1952, MNRAS, 112, 195

  7. [7]

    & Hoyle, F

    Bondi, H. & Hoyle, F. 1944, MNRAS, 104, 273

  8. [8]

    Booth, C. M. & Schaye, J. 2009, MNRAS, 398, 53 Brüggen, M., Scannapieco, E., & Grete, P. 2023, ApJ, 951, 113

  9. [9]

    Butcher, J. C. 2008, Numerical Methods for Ordinary Differen- tial Equations, 2nd edn. (John Wiley & Sons)

  10. [10]

    C., et al

    Cammelli, V ., Monaco, P., Tan, J. C., et al. 2025, MNRAS, 536, 851

  11. [11]

    2025, A&A, 700, A197

    Castignani, G., Combes, F., Salomé, P., Edge, A., & Jablonka, P. 2025, A&A, 700, A197

  12. [12]

    & Teyssier, R

    Cattaneo, A. & Teyssier, R. 2007, MNRAS, 376, 1547

  13. [13]

    W., Donahue, M., V oit, G

    Cavagnolo, K. W., Donahue, M., V oit, G. M., & Sun, M. 2009, ApJS, 182, 12

  14. [14]

    K., Schive, H.-Y ., ZuHone, J., & Gas- pari, M

    Chen, S.-S., Yang, H.-Y . K., Schive, H.-Y ., ZuHone, J., & Gas- pari, M. 2024, arXiv e-prints, arXiv:2412.13595

  15. [15]

    S., Su, K.-Y ., Narayan, R., & Natarajan, P

    Cho, H., Prather, B. S., Su, K.-Y ., Narayan, R., & Natarajan, P. 2024, ApJ, 977, 200 Di Matteo, T., Springel, V ., & Hernquist, L. 2005, Nature, 433, 604

  16. [16]

    2015, ApJ, 805, 177

    Donahue, M., Connor, T., Fogarty, K., et al. 2015, ApJ, 805, 177

  17. [17]

    2014, MNRAS, 444, 1453 Dupourqué, S., Clerc, N., Pointecouteau, E., et al

    Dubois, Y ., Pichon, C., Welker, C., et al. 2014, MNRAS, 444, 1453 Dupourqué, S., Clerc, N., Pointecouteau, E., et al. 2024, A&A, 687, A58

  18. [18]

    Eckert, D., Gaspari, M., Gastaldello, F., Le Brun, A. M. C., & O’Sullivan, E. 2021, Universe, 7, 142

  19. [19]

    2014, Journal of Paral- lel and Distributed Computing, 74

    Edwards, H., Trott, C., & Sunderland, D. 2014, Journal of Paral- lel and Distributed Computing, 74

  20. [20]

    S., Davis, T

    Elford, J. S., Davis, T. A., Ruffa, I., et al. 2024, MNRAS, 528, 319

  21. [21]

    2024, MNRAS, 527, 1317

    Eskenasy, R., Olivares, V ., Su, Y ., & Li, Y . 2024, MNRAS, 527, 1317

  22. [22]

    Fabian, A. C. 1994, ARA&A, 32, 277

  23. [23]

    Fabian, A. C. 2012, ARA&A, 50, 455

  24. [24]

    C., Johnstone, R

    Fabian, A. C., Johnstone, R. M., Sanders, J. S., et al. 2008, Na- ture, 454, 968 Ferrière, K. M. 2001, Reviews of Modern Physics, 73, 1031

  25. [25]

    Field, G. B. 1965, ApJ, 142, 531

  26. [26]

    2017, A&A, 601, A143

    Fiore, F., Feruglio, C., Shankar, F., et al. 2017, A&A, 601, A143

  27. [27]

    2015, ApJ, 813, 117

    Fogarty, K., Postman, M., Connor, T., Donahue, M., & Mous- takas, J. 2015, ApJ, 813, 117

  28. [28]

    W., & O’Shea, B

    Fournier, M., Grete, P., Brüggen, M., Glines, F. W., & O’Shea, B. W. 2024, A&A, 691, A239

  29. [29]

    2025, A&A, 698, A121

    Fournier, M., Grete, P., Brüggen, M., et al. 2025, A&A, 698, A121

  30. [30]

    2015, A&A, 579, A62

    Gaspari, M., Brighenti, F., & Temi, P. 2015, A&A, 579, A62

  31. [31]

    & Churazov, E

    Gaspari, M. & Churazov, E. 2013, A&A, 559, A78

  32. [32]

    L., et al

    Gaspari, M., McDonald, M., Hamer, S. L., et al. 2018, ApJ, 854, 167

  33. [33]

    Gaspari, M., Ruszkowski, M., & Oh, S. P. 2013, MNRAS, 432, 3401

  34. [34]

    2012, ApJ, 746, 94

    Gaspari, M., Ruszkowski, M., & Sharma, P. 2012, ApJ, 746, 94

  35. [35]

    & S˛ adowski, A

    Gaspari, M. & S˛ adowski, A. 2017, ApJ, 837, 149

  36. [36]

    2017, MNRAS, 466, 677

    Gaspari, M., Temi, P., & Brighenti, F. 2017, MNRAS, 466, 677

  37. [37]

    2020, Nature Astronomy, 4, 10

    Gaspari, M., Tombesi, F., & Cappi, M. 2020, Nature Astronomy, 4, 10

  38. [38]

    Godunov, S. K. 1959, Math. Sbornik, 47, 271

  39. [39]

    C., Miller, J

    Grete, P., Dolence, J. C., Miller, J. M., et al. 2023, The Interna- tional Journal of High Performance Computing Applications, 37, 465

  40. [40]

    W., & Beckwith, K

    Grete, P., O’Shea, B. W., & Beckwith, K. 2018, ApJ, 858, L19

  41. [41]

    2025, ApJ, 987, 122

    Grete, P., Scannapieco, E., Brüggen, M., & Pan, L. 2025, ApJ, 987, 122

  42. [42]

    M., Kim, C.-G., & Quataert, E

    Guo, M., Stone, J. M., Kim, C.-G., & Quataert, E. 2023, ApJ, 946, 26

  43. [43]

    M., Quataert, E., & Kim, C.-G

    Guo, M., Stone, J. M., Quataert, E., & Kim, C.-G. 2024, ApJ, 973, 141

  44. [44]

    1990, ApJ, 356, 359 Hitomi Collaboration, Aharonian, F., Akamatsu, H., et al

    Hernquist, L. 1990, ApJ, 356, 359 Hitomi Collaboration, Aharonian, F., Akamatsu, H., et al. 2016, Nature, 535, 117

  45. [45]

    S., Nandra, K., Clerc, N., & Gaspari, M

    Hofmann, F., Sanders, J. S., Nandra, K., Clerc, N., & Gaspari, M. 2016, A&A, 585, A130

  46. [46]

    F., Gurvich, A

    Hopkins, P. F., Gurvich, A. B., Shen, X., et al. 2023, MNRAS, 525, 2241

  47. [47]

    F., Wetzel, A., Kereš, D., et al

    Hopkins, P. F., Wetzel, A., Kereš, D., et al. 2018, MNRAS, 477, 1578

  48. [48]

    G., Starkenburg, T

    Iyer, K. G., Starkenburg, T. K., Bryan, G. L., et al. 2025, ApJ, 994, 174

  49. [49]

    J., Babul, A., Davé, R., Cui, W., & Rennehan, D

    Jennings, F. J., Babul, A., Davé, R., Cui, W., & Rennehan, D. 2025, MNRAS, 536, 145 Juráˇnová, A., Werner, N., Nulsen, P. E. J., et al. 2020, MNRAS, 499, 5163

  50. [50]

    & Gaspari, M

    Khatri, R. & Gaspari, M. 2016, MNRAS, 463, 655

  51. [51]

    2020, MNRAS, 492, 2095

    Kim, D.-W., Traynor, L., Paggi, A., et al. 2020, MNRAS, 492, 2095

  52. [52]

    & Pounds, K

    King, A. & Pounds, K. 2015, ARA&A, 53, 115

  53. [53]

    Kormendy, J. & Ho, L. C. 2013, ARA&A, 51, 511

  54. [54]

    W., et al

    Koss, M., Aftab, N., Allen, S. W., et al. 2025, arXiv e-prints, arXiv:2511.00253

  55. [55]

    Kravtsov, A. V . & Borgani, S. 2012, ARA&A, 50, 353

  56. [56]

    Li, J., Emonts, B. H. C., Cai, Z., et al. 2021, ApJ, 922, L29

  57. [57]

    1969, Nature, 223, 690

    Lynden-Bell, D. 1969, Nature, 223, 690

  58. [58]

    M., Morganti, R., Oosterloo, T

    Maccagni, F. M., Morganti, R., Oosterloo, T. A., & Mahony, E. K. 2014, A&A, 571, A67

  59. [59]

    M., Morganti, R., Oosterloo, T

    Maccagni, F. M., Morganti, R., Oosterloo, T. A., Oonk, J. B. R., & Emonts, B. H. C. 2018, A&A, 614, A42

  60. [60]

    M., Serra, P., Gaspari, M., et al

    Maccagni, F. M., Serra, P., Gaspari, M., et al. 2021, A&A, 656, A45

  61. [61]

    Marinacci, F., Grand, R. J. J., Pakmor, R., et al. 2017, MNRAS, 466, 3859

  62. [62]

    McCourt, M., Sharma, P., Quataert, E., & Parrish, I. J. 2012, MNRAS, 419, 3319

  63. [63]

    R., & Tremblay, G

    McDonald, M., Gaspari, M., McNamara, B. R., & Tremblay, G. R. 2018, ApJ, 858, 45

  64. [64]

    J., Gaspari, M., et al

    McKinley, B., Tingay, S. J., Gaspari, M., et al. 2022, Nature Astronomy, 6, 109

  65. [65]

    McNamara, B. R. & Nulsen, P. E. J. 2012, New Journal of Physics, 14, 055023

  66. [66]

    2023, A&A, 678, A42

    Morganti, R., Murthy, S., Oosterloo, T., et al. 2023, A&A, 678, A42

  67. [67]

    & Ostriker, J

    Naab, T. & Ostriker, J. P. 2017, ARA&A, 55, 59

  68. [68]

    The Hot and Energetic Universe: A White Paper presenting the science theme motivating the Athena+ mission

    Nandra, K., Barret, D., Barcons, X., et al. 2013, arXiv e-prints, arXiv:1306.2307

  69. [69]

    F., Frenk, C

    Navarro, J. F., Frenk, C. S., & White, S. D. 1997, ApJ, 490, 493 Article number, page 22 of 23 Filippo Barbani et al.: Chaotic cold accretion from halo rain to sub-pc feeding

  70. [70]

    2025, Nature Astron- omy, 9, 449

    Olivares, V ., Picquenot, A., Su, Y ., et al. 2025, Nature Astron- omy, 9, 449

  71. [71]

    2019, A&A, 631, A22

    Olivares, V ., Salome, P., Combes, F., et al. 2019, A&A, 631, A22

  72. [72]

    L., et al

    Olivares, V ., Salomé, P., Hamer, S. L., et al. 2022, A&A, 666, A94

  73. [73]

    2023, ApJ, 954, 56

    Olivares, V ., Su, Y ., Forman, W., et al. 2023, ApJ, 954, 56

  74. [74]

    K., Di Mascolo, L., et al

    Orlowski-Scherer, J., Haridas, S. K., Di Mascolo, L., et al. 2022, A&A, 667, L6 O’Sullivan, E., Rajpurohit, K., Schellenberger, G., et al. 2024, ApJ, 970, 65

  75. [75]

    Piana, O., Dayal, P., V olonteri, M., & Choudhury, T. R. 2021, MNRAS, 500, 2146

  76. [76]

    & Pu, H.-Y

    Piana, O. & Pu, H.-Y . 2025, Universe, 11, 78

  77. [77]

    2019, MNRAS, 490, 3196

    Pillepich, A., Nelson, D., Springel, V ., et al. 2019, MNRAS, 490, 3196

  78. [78]

    S., Werner, N., et al

    Pinto, C., Sanders, J. S., Werner, N., et al. 2015, A&A, 575, A38

  79. [79]

    & Soker, N

    Pizzolato, F. & Soker, N. 2005, ApJ, 632, 821

  80. [80]

    2025, ApJ, 984, 120

    Rajpurohit, K., Deb, T., Kolokythas, K., et al. 2025, ApJ, 984, 120

Showing first 80 references.